class_docstr: Class for the manifold of geometric distributions.
  
  This is the parameter space of geometric distributions
  i.e. [0,1] segment.
docstr: Compute pmf associated to point.
  
  Compute the probability mass function of the geometric
  distribution with parameters provided by point.
  
  Parameters
  ----------
  point : array-like, shape=[..., 1]
      Point representing an geometric distribution (scale).
  
  Returns
  -------
  pdf : function
      Probability mass function of the geometric distribution with
      scale parameter provided by point.
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code: def point_to_pdf(self, point):
      """Compute pmf associated to point.
  
      Compute the probability mass function of the geometric
      distribution with parameters provided by point.
  
      Parameters
      ----------
      point : array-like, shape=[..., 1]
          Point representing an geometric distribution (scale).
  
      Returns
      -------
      pdf : function
          Probability mass function of the geometric distribution with
          scale parameter provided by point.
      """
  
      def pmf(k):
          """Generate parameterized function for geometric pmf.
  
          Compute the probability mass function of the geometric
          distribution with parameters provided by point.
  
          Parameters
          ----------
          k : array-like, shape=[n_samples,]
              Point in the sample space, i.e. an integer.
  
          Returns
          -------
          pmf_at_k : array-like, shape=[..., n_samples]
              Probability mass function of the geometric distribution with
              parameters provided by point.
          """
          k = gs.reshape(gs.array(k), (-1,))
          return (1 - point) ** (k - 1) * point
  
      return pmf
  
imports: from scipy.stats import geom
  import geomstats.backend
  from geomstats.geometry.base import VectorSpaceOpenSet
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.information_geometry.base import InformationManifoldMixin, ScipyUnivariateRandomVariable
label_desc: Use image node_id 7 for calling the GeometricDistributions obj's underlying member method code with example usage: obj.point_to_pdf(point) and returns: pmf, unknown